% Key papers for Learned embeddings for retrieval (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2018_deep_28709,
  title = {{Deep Active Learning for Named Entity Recognition}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/125},
}

@inproceedings{iclr2021_autoregressive_30006,
  title = {{Autoregressive Entity Retrieval}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2642},
}

@inproceedings{cvpr2016_efficient_11513,
  title = {{Efficient Indexing of Billion-Scale Datasets of Deep Descriptors}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{iclr2020_selection_29452,
  title = {{Selection via Proxy: Efficient Data Selection for Deep Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HJg2b0VYDr},
}

@inproceedings{aaai2018_argument_106004,
  title = {{Argument Mining for Improving the Automated Scoring of Persuasive Essays}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12046},
}

@inproceedings{neurips2022_transformer_65134,
  title = {{Transformer Memory as a Differentiable Search Index}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53008},
}

@inproceedings{aaai2017_definition_105874,
  title = {{Definition Modeling: Learning to Define Word Embeddings in Natural Language}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10996},
}

@inproceedings{cvpr2016_efficient_11515,
  title = {{Efficient Large-Scale Approximate Nearest Neighbor Search on the GPU}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2016_joint_55798,
  title = {{Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7157},
}

@inproceedings{neurips2017_hash_56356,
  title = {{Hash Embeddings for Efficient Word Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9269},
}

@inproceedings{cvpr2017_amvh_12034,
  title = {{AMVH: Asymmetric Multi-Valued Hashing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2022_a_65604,
  title = {{A Neural Corpus Indexer for Document Retrieval}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54771},
}

@inproceedings{icml2018_learning_36790,
  title = {{Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2284},
}

@inproceedings{neurips2019_extreme_58249,
  title = {{Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14265},
}

@inproceedings{icml2020_differentiable_38104,
  title = {{Differentiable Product Quantization for End-to-End Embedding Compression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6429},
}

@inproceedings{neurips2019_what_59197,
  title = {{What the Vec? Towards Probabilistically Grounded Embeddings}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13830},
}

@inproceedings{cvpr2018_a_12801,
  title = {{A Neural Multi-Sequence Alignment TeCHnique (NeuMATCH)}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Dogan_A_Neural_Multi-Sequence_CVPR_2018_paper.html},
}

@inproceedings{aaai2018_training_106002,
  title = {{Training and Evaluating Improved Dependency-Based Word Embeddings}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12044},
}

@inproceedings{icml2018_efficient_36667,
  title = {{Efficient end-to-end learning for quantizable representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2123},
}

@inproceedings{neurips2025_sparse_80476,
  title = {{Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=zugMif2nm6},
}

@inproceedings{cvpr2024_bridging_22878,
  title = {{Bridging the Gap Between End-to-End and Two-Step Text Spotting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29860},
}

@inproceedings{aaai2025_drughash_8818,
  title = {{DrugHash: Hashing Based Contrastive Learning for Virtual Screening}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33873},
}

@inproceedings{aaai2025_distribution_8771,
  title = {{Distribution-Driven Dense Retrieval: Modeling Many-to-One Query-Document Relationship}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33299},
}

@inproceedings{cvpr2025_lotusfilter_26822,
  title = {{LotusFilter: Fast Diverse Nearest Neighbor Search via a Learned Cutoff Table}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33979},
}

@inproceedings{icml2026_onesearch_51165,
  title = {{OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=JKGgHY9FKa},
}

@inproceedings{iclr2024_implicitslim_33696,
  title = {{ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19379},
}

@inproceedings{icml2025_banyan_46078,
  title = {{Banyan: Improved Representation Learning with Explicit Structure}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46480},
}

@inproceedings{icml2026_lemur_49359,
  title = {{LEMUR: Learned Multi-Vector Retrieval}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=1mpoh36RBU},
}

@inproceedings{icml2026_localized_53329,
  title = {{Localized, High-resolution Geographic Representations with Slepian Functions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=eWQQ0tO0kB},
}

@inproceedings{icml2026_no_54519,
  title = {{No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=pp1enKGv2v},
}

@inproceedings{neurips2025_dodo_79184,
  title = {{DoDo-Code: an Efficient Levenshtein Distance Embedding-based Code for 4-ary IDS Channel}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=mgURpQ4NXO},
}

@inproceedings{neurips2025_reconciling_79221,
  title = {{Reconciling Geospatial Prediction and Retrieval via Sparse Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=n6AfpsbD7n},
}

@inproceedings{iclr2025_semi_83267,
  title = {{Semi-Parametric Retrieval via Binary Bag-of-Tokens Index}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28545},
}

@inproceedings{iclr2025_ese_83534,
  title = {{ESE: Espresso Sentence Embeddings}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28282},
}

@inproceedings{neurips2026_strable_89921,
  title = {{STRABLE: Benchmarking Tabular Machine Learning with Strings}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/139430},
}

@inproceedings{neurips2026_your_92891,
  title = {{Your Embedding Model Is SMARTer Than You Think}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152683},
}

@inproceedings{aaai2026_glyphshield_100022,
  title = {{GlyphShield: Document Watermarking for the Physical World via Vector Typeface Synthesis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37073},
}

@inproceedings{aaai2026_self_106230,
  title = {{Self-Improving Sparse Retrieval Through Heuristic Representation Refinement and Representation-Focused Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38537},
}

@inproceedings{aaai2026_on_106543,
  title = {{On Coresets for End-to-end Learning from Crowds}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38850},
}